Run: 2026-07-25-01KYD5SYCYCFA6BW66XZ6VTWBC

Run Details

Duration:
1m 15s
Cost:
$0.028841
Provider:
Moonshot AI

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<codex> <character id="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist"> <eyeColor>brown</eyeColor> <hair>closely cropped salt-and-pepper</hair> <height>5'9"</height> <age>41</age> <jawline>sharp jaw</jawline> <watch>worn leather watch on her left wrist</watch> <bearing>military precision</bearing> <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description> <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory> </character> <character id="4417" name="Tomás Herrera" aliases="Tommy, Tomás, Herrera" pronouns="he/him" species="Human" storyRole="Support"> <eyeColor>warm brown</eyeColor> <hair>short curly dark brown</hair> <height>5'10"</height> <age>29</age> <skinTone>olive skin</skinTone> <scar>scar running along his left forearm from a knife attack</scar> <medallion>Saint Christopher medallion around his neck</medallion> <birthplace>Seville, Spain</birthplace> <description>A former paramedic who provides off-the-books medical care for the clique.</description> <backstory>Born in Seville, Spain. He moved to London to work for the NHS but lost his license after administering unauthorized treatments to supernatural patients.</backstory> </character> <location id="854" name="The Raven's Nest" aliases="the Nest, Raven, Silas' bar" realm="Earth"> <signColor>distinctive green neon sign above the entrance</signColor> <secretRoom>hidden back room accessible through a bookshelf, used for clandestine meetings</secretRoom> <description>A dimly lit bar in Soho, London. The walls are covered with old maps and black-and-white photographs.</description> </location> <location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth"> <currentLocation>abandoned Tube station beneath Camden</currentLocation> <entryRequirement>bone token</entryRequirement> <schedule>moves locations every full moon</schedule> <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description> </location> </codex> Write a fully fleshed out scene of at least 1000 words in the thriller genre. A detective is pursuing a suspect through rain-soaked city streets at night. The chase takes them from the street level down into an underground market. The detective must decide whether to follow the suspect into unfamiliar and potentially dangerous territory. Use the codex entries above as your world reference for characters and setting. Only include the prose of the scene without any markdown or commentary.

Model response

AI
The rain had been falling since midnight, and Detective Harlow Quinn had been running for six blocks. Ahead of her, the suspect cut left off Brewer Street, shoulder slamming into a cafe's shutter as he took the corner too fast. He recovered without looking back. They never looked back until they were scared, and Tomás Herrera was very scared. "Stop! Police!" She'd shouted it four times now. Each time, her voice came back flatter, swallowed by the rain and the low rumble of Soho's after-midnight traffic. Nobody stopped for anything in this part of London at one in the morning. That was half the reason the clique had chosen it. Herrera splashed through a standing puddle where the drain had clogged with leaves, his boots sending up sheets of dirty water. He was quick for a man she'd always pegged as the soft one. Twenty-nine years old, olive-skinned, a Saint Christopher medallion she'd seen glinting at his throat a dozen times in surveillance photos. A former paramedic who'd lost his license for treating patients that didn't exist in any NHS registry. Quinn had built her file on him over eleven months, and not once had he run. Tonight, something had changed. Tonight she'd watched him carry a bleeding man into the Raven's Nest and come out forty minutes later with a canvas bag that dripped, and when she'd stepped out of her car and said his name, he'd bolted like a man with the devil behind him. Maybe that was closer to the truth than she knew. "Tomás!" she tried, dropping the formality. "I just want to talk!" He glanced back then — just once — and his face under the streetlight was pale and wet and twisted with something that didn't look like guilt. It looked like pity. Then he was gone again, down an alley between a shuttered noodle shop and a doorway stinking of piss. Quinn followed. Her left wrist ached where her old leather watch dug in as she ran, the one Morris had given her the Christmas before he died. Three years, and the strap still smelled faintly of his cologne when it got wet. She ran with her jaw set and her breath measured, the old military discipline her body never forgot even at forty-one. She was faster than Herrera. She'd been closing the gap for two blocks. The alley bent. Herrera burst out onto Berwick Street, dodged a black cab that leaned on its horn, and vanished into the covered market's south entrance. Quinn followed between the stalls — tarps snapping in the wind, empty trays, a fox that scattered from a bin — and burst out the far side in time to see him duck down a stairwell beneath a rusted sign she couldn't read in the dark. Not the Nest. She'd assumed he was running for Silas' bar, for the green neon and whatever waited behind its bookshelf. Instead he'd gone down. She reached the stairwell mouth and stopped. The stairs descended into darkness — old tiles, curved walls, a Underground roundel so faded she could barely make out the bar through the circle. Camden Town, it said, though they were a mile and a half from Camden. Quinn stood at the top of the steps with rain streaming off her cropped hair and felt the first real doubt of the night settle between her shoulder blades. This was wrong. All of it was wrong, and she knew it the way she'd known things in the army — the way she'd known, three years ago, that the warehouse where Morris died was wrong before they ever kicked the door. She'd ignored it then. Below, footsteps echoed. Herrera was still moving, deeper, his pace sure now, unhurried. As if he'd reached sanctuary. As if the street above had been the dangerous part and this was safety. Quinn keyed her radio. Static. She looked at the display: no signal, though she'd had four bars on Berwick Street. She looked at her phone. No service. The little clock said 1:14, and then, as she watched, it flickered and said 1:14 again, and again, as if the minute had forgotten how to pass. "Christ," she breathed. She should call it in. Walk back to the car, get signal, request backup, do it by the book — the book she'd been bending for eleven months on a case her DCI had twice told her to drop. The clique. The impossible surveillance gaps. The witnesses who described men whose faces she could never quite hold in her memory afterward. And Morris, always Morris, dead in a warehouse of injuries the coroner had written up as "consistent with an industrial accident" with a straight face and shaking hands. Herrera was down there. The man who patched up the people she couldn't catch. The man who might know — might actually know — what had happened to her partner. Quinn checked her sidearm, pulled her coat straight, and went down. The stairs went deeper than any Tube station had a right to. The tiles changed as she descended — Victorian green giving way to something older, grey stone sweating with moisture, carved with symbols she told herself were graffiti. The air warmed. The rain-sound faded behind her until there was nothing but her footsteps and a low murmur ahead, like a crowd heard through a wall. Then the stairs ended at an archway, and Quinn stopped again. Beyond it, the old platform stretched away into lamplight — actual gas lamps, hissing softly on iron posts — and between them, stalls. Dozens of them, filling the platform edge to edge, built from driftwood and brass and bone-white canvas. And people. If they were people. A woman with too many joints in her fingers was weighing something on a brass scale. A man in a bowler hat turned to watch her arrive, and his eyes caught the lamplight like a dog's. The smell hit her all at once: incense and copper and wet earth and something sweetly rotten underneath, like flowers left too long in a vase. The Veil Market. She didn't know the name yet, but she knew what she was looking at. Eleven months of impossible gaps, and here was the gap, opened up like a mouth. A figure waited just past the archway, beside a stall selling jars of cloudy liquid. Herrera. He'd stopped running. He stood with his hands loose at his sides, the medallion bright at his throat, and he watched her the way you'd watch someone step off a curb in front of a bus. "You shouldn't have followed me, Detective," he said. His voice carried that soft Sevillian lilt she'd heard on the wiretaps. "I was trying to keep you out of this. That's all the running was. I swear it on my mother's grave." "Tomás Herrera," Quinn said, and her voice came out steadier than she felt. "You're under caution. You don't have to say anything—" "Stop." He said it gently. Not a threat. A plea. "Look around you. Really look. And then decide which one of us is in danger." She didn't want to look. Looking felt like admitting something. But Harlow Quinn had spent eighteen years training herself to look at the worst thing first, so she turned her head and let herself see it — the stall selling teeth that were too long, the child-sized figure with grey skin haggling over a bottle, the man at the far end of the platform whose shadow pointed the wrong way. Her hand found her sidearm. She didn't draw it. Some deep animal part of her understood that drawing it would be the end. "What is this place?" she asked. "The kind of place that eats people like you," Herrera said. "The kind of place your partner found, three years ago. Morris, yes? DS Morris? He came down somewhere like this chasing someone like me, and he didn't have anyone to warn him." He took a breath, and his dark eyes were full of that terrible pity again. "I'm the only reason you know his death wasn't an accident, Detective. I've read what you really are to this city. Now you have a choice, and you have about thirty seconds to make it. Walk back up those stairs, forget you saw me tonight, and live long enough to learn the truth slowly. Or stay, and learn it all at once — the way he did." Behind her, the stairwell stood dark and open. The rain was still falling up there, somewhere, on a London that made sense. Quinn thought of Morris's watch ticking on her wrist, counting out a minute that had already forgotten itself once tonight. She thought about turning around. She genuinely did. Then she stepped forward, past Herrera, onto the platform, into the lamplight and the wrong shadows and the smell of copper and old flowers. "Show me," she said.
created_at"2026-07-25T17:40:12.326Z" 7/25/2026, 5:40:12 PM
model"moonshotai/kimi-k3-20260715"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3239
moderation_latency(null)
generation_time75391
tokens_prompt888
tokens_completion2128
native_tokens_prompt910
native_tokens_completion1879
native_tokens_completion_images(null)
native_tokens_reasoning24
native_tokens_cached768
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
service_tier(null)
usage0.0288414
router(null)
provider_responses
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endpoint_id"650c9b12-7b6d-444d-8d92-df8daef84d7a"
id"chatcmpl-6a64f4e9807af92158ea17d7"
is_byokfalse
latency3239
model_permaslug"moonshotai/kimi-k3-20260715"
provider_name"Moonshot AI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1785001212-dwqzQ6ESUCzg4MyMkd3u"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1785001212-q2E72lDF6CjBTJtVS09S"
upstream_id"chatcmpl-6a64f4e9807af92158ea17d7"
total_cost0.0288414
cache_discount0.0020736
upstream_inference_cost0
provider_name"Moonshot AI"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags12
adverbTagCount0
adverbTags(empty)
dialogueSentences16
tagDensity0.75
leniency1
rawRatio0
effectiveRatio0
76.29% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1476
totalAiIsmAdverbs7
found
0
adverb"very"
count1
1
adverb"softly"
count1
2
adverb"sweetly"
count1
3
adverb"gently"
count1
4
adverb"really"
count2
5
adverb"slowly"
count1
highlights
0"very"
1"softly"
2"sweetly"
3"gently"
4"really"
5"slowly"
100.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
66.12% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1476
totalAiIsms10
found
0
word"glinting"
count1
1
word"measured"
count1
2
word"streaming"
count1
3
word"footsteps"
count2
4
word"echoed"
count1
5
word"sanctuary"
count1
6
word"flickered"
count1
7
word"lilt"
count1
8
word"grave"
count1
highlights
0"glinting"
1"measured"
2"streaming"
3"footsteps"
4"echoed"
5"sanctuary"
6"flickered"
7"lilt"
8"grave"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences101
matches(empty)
86.28% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount3
hedgeCount1
narrationSentences101
filterMatches
0"watch"
1"see"
hedgeMatches
0"happened to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences106
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen66
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1490
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions16
unquotedAttributions1
matches
0"Camden Town, it said, though they were a mile and a half from Camden."
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions53
wordCount1296
uniqueNames24
maxNameDensity0.85
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Detective1
Harlow2
Quinn11
Brewer1
Street3
Tomás1
Herrera9
Soho1
London2
Saint1
Christopher1
Raven1
Nest2
Morris5
Christmas1
Berwick2
Underground1
Town1
Camden2
Tube1
Victorian1
Veil1
Market1
Sevillian1
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Saint"
5"Christopher"
6"Morris"
places
0"Brewer"
1"Street"
2"Soho"
3"London"
4"Raven"
5"Berwick"
6"Town"
7"Camden"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences60
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1490
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences106
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs35
mean42.57
std33.87
cv0.796
sampleLengths
017
142
251
3137
410
511
650
776
872
925
107
1168
1246
1332
1454
153
1689
1730
1811
1966
2011
21108
2232
2352
2441
2522
2625
2770
2823
296
30125
3142
328
3324
344
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences101
matches
0"was gone"
46.39% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs217
matches
0"was running"
1"was still moving"
2"was weighing"
3"was looking"
4"was still falling"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount13
semicolonCount0
flaggedSentences9
totalSentences106
ratio0.085
matches
0"He glanced back then — just once — and his face under the streetlight was pale and wet and twisted with something that didn't look like guilt."
1"Quinn followed between the stalls — tarps snapping in the wind, empty trays, a fox that scattered from a bin — and burst out the far side in time to see him duck down a stairwell beneath a rusted sign she couldn't read in the dark."
2"The stairs descended into darkness — old tiles, curved walls, a Underground roundel so faded she could barely make out the bar through the circle."
3"All of it was wrong, and she knew it the way she'd known things in the army — the way she'd known, three years ago, that the warehouse where Morris died was wrong before they ever kicked the door."
4"Walk back to the car, get signal, request backup, do it by the book — the book she'd been bending for eleven months on a case her DCI had twice told her to drop."
5"The man who might know — might actually know — what had happened to her partner."
6"The tiles changed as she descended — Victorian green giving way to something older, grey stone sweating with moisture, carved with symbols she told herself were graffiti."
7"Beyond it, the old platform stretched away into lamplight — actual gas lamps, hissing softly on iron posts — and between them, stalls."
8"But Harlow Quinn had spent eighteen years training herself to look at the worst thing first, so she turned her head and let herself see it — the stall selling teeth that were too long, the child-sized figure with grey skin haggling over a bottle, the man at the far end of the platform whose shadow pointed the wrong way."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount616
adjectiveStacks0
stackExamples(empty)
adverbCount24
adverbRatio0.03896103896103896
lyAdverbCount5
lyAdverbRatio0.008116883116883116
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences106
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences106
mean14.06
std12.35
cv0.879
sampleLengths
017
123
25
314
48
519
614
710
821
913
1020
1117
1216
134
1446
1510
166
175
1827
194
2019
212
2225
2315
2421
255
268
273
2823
2946
303
3118
324
337
3425
3514
3629
373
3839
394
403
4110
425
4314
444
451
4615
475
482
4927
57.23% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats16
diversityRatio0.4339622641509434
totalSentences106
uniqueOpeners46
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount5
totalSentences89
matches
0"Maybe that was closer to"
1"Then he was gone again,"
2"Instead he'd gone down."
3"Then the stairs ended at"
4"Then she stepped forward, past"
ratio0.056
94.16% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount28
totalSentences89
matches
0"He recovered without looking back."
1"They never looked back until"
2"She'd shouted it four times"
3"He was quick for a"
4"she tried, dropping the formality"
5"He glanced back then —"
6"It looked like pity."
7"Her left wrist ached where"
8"She ran with her jaw"
9"She was faster than Herrera."
10"She'd been closing the gap"
11"She'd assumed he was running"
12"She reached the stairwell mouth"
13"She'd ignored it then."
14"She looked at the display:"
15"She looked at her phone."
16"She should call it in."
17"She didn't know the name"
18"He'd stopped running."
19"He stood with his hands"
ratio0.315
77.98% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount68
totalSentences89
matches
0"The rain had been falling"
1"He recovered without looking back."
2"They never looked back until"
3"She'd shouted it four times"
4"Each time, her voice came"
5"Nobody stopped for anything in"
6"That was half the reason"
7"Herrera splashed through a standing"
8"He was quick for a"
9"A former paramedic who'd lost"
10"Quinn had built her file"
11"Tonight, something had changed."
12"Tonight she'd watched him carry"
13"she tried, dropping the formality"
14"He glanced back then —"
15"It looked like pity."
16"Her left wrist ached where"
17"She ran with her jaw"
18"She was faster than Herrera."
19"She'd been closing the gap"
ratio0.764
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount3
totalSentences89
matches
0"As if he'd reached sanctuary."
1"As if the street above"
2"If they were people."
ratio0.034
87.91% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences52
technicalSentenceCount4
matches
0"A former paramedic who'd lost his license for treating patients that didn't exist in any NHS registry."
1"He glanced back then — just once — and his face under the streetlight was pale and wet and twisted with something that didn't look like guilt."
2"But Harlow Quinn had spent eighteen years training herself to look at the worst thing first, so she turned her head and let herself see it — the stall selling t…"
3"Quinn thought of Morris's watch ticking on her wrist, counting out a minute that had already forgotten itself once tonight."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags12
uselessAdditionCount0
matches(empty)
87.50% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags7
fancyCount1
fancyTags
0"she breathed (breathe)"
dialogueSentences16
tagDensity0.438
leniency0.875
rawRatio0.143
effectiveRatio0.125
89.3287%